Updated Multiple Linear Regression Models for Predicting Chronic Aluminum Toxicity to Freshwater Aquatic Organisms and Developing Water Quality Guidelines

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Abstract

Abstract Multiple linear regression (MLR) models for predicting chronic aluminum toxicity to a cladoceran (Ceriodaphnia dubia) and a fish (Pimephales promelas) as a function of 3 toxicity-modifying factors (TMFs)—dissolved organic carbon (DOC), pH, and hardness—have been published previously. However, the range over which data for these TMFs were available was somewhat limited. To address this limitation, additional chronic toxicity tests with these species were subsequently conducted to expand the DOC range up to 12 mg/L, the pH range up to 8.7, and the hardness range up to 428 mg/L. The additional toxicity data were used to update the chronic MLR models. The adjusted R2 for the C. dubia 20% effect concentration (EC20) model increased from 0.71 to 0.92 with the additional toxicity data, and the predicted R2 increased from 0.57 to 0.89. For P. promelas, the adjusted R2 increased from 0.87 to 0.92 and the predicted R2 increased from 0.72 to 0.87. The high predicted R2 relative to the adjusted R2 indicates that the models for both species are not overly parameterized. When data for C. dubia and P. promelas were pooled, the adjusted R2 values were comparable to the species-specific models (0.90 and 0.88 for C. dubia and P. promelas, respectively). This indicates that chronic aluminum EC20s for C. dubia and P. promelas respond similarly to variation in DOC, pH, and hardness. Overall, the pooled model predicted EC20s that were within a factor of 2 of observed in 100% of the C. dubia tests and 94% of the P. promelas tests. Environ Toxicol Chem 2020;39:1724–1736. © 2020 SETAC

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